Romain Couillet
25 papers · 2016–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (14) π Academic Marathon (9)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π
Renaissance Researcher
(7)
π
Triple Crown
π§¬
Topic Evolution
π
Keyword Champion
(4)
π₯
Unstoppable
(6)
π
Century Club
(25)
ποΈ
Keyword Collector
(90)
β‘
Prolific Year
(5)
Conferences
ICML (8)
JMLR (6)
ICLR (4)
NIPS (3)
AISTATS (2)
CONLL (1)
EMNLP (1)
Top co-authors
Keywords
random matrix theory
(9)
random matrix
(8)
spectral clustering
(7)
gaussian mixture model
(5)
community detection
(5)
spectral analysis
(4)
graph theory
(4)
kernel matrix
(3)
word embedding
(2)
principal component analysis
(2)
high dimensional datum
(2)
multi-task learning
(2)
natural language processing
(2)
asymptotic analysis
(2)
semi-supervised learning
(2)
representation learning
(2)
network analysis
(2)
tensor decomposition
(2)
stochastic block model
(2)
echo state network
(2)
Papers
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
JMLR 2025
PCA-based Multi-Task Learning: a Random Matrix Approach
ICML 2023
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture
AISTATS 2023
A Random Matrix Perspective on Random Tensors
JMLR 2022
Random matrices in service of ML footprint: ternary random features with no performance loss
ICLR 2022
A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources
ICML 2022
Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering
ICML 2021
Consistent Semi-Supervised Graph Regularization for High Dimensional Data
JMLR 2021
The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers
AISTATS 2021
Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
ICLR 2021
Sparse Quantized Spectral Clustering
ICLR 2021
A Unified Framework for Spectral Clustering in Sparse Graphs
JMLR 2021
Word Representations Concentrate and This is Good News!
EMNLP 2020
Word Representations Concentrate and This is Good News!
CONLL 2020
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent
NIPS 2020
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
ICML 2020
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
NIPS 2020
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs
NIPS 2019
A Kernel Random Matrix-Based Approach for Sparse PCA
ICLR 2019
Random Matrix Improved Covariance Estimation for a Large Class of Metrics
ICML 2019
Improved spectral community detection in large heterogeneous networks
JMLR 2018
The Dynamics of Learning: A Random Matrix Approach
ICML 2018
On the Spectrum of Random Features Maps of High Dimensional Data
ICML 2018
The Asymptotic Performance of Linear Echo State Neural Networks
JMLR 2016
A Random Matrix Approach to Echo-State Neural Networks
ICML 2016